Alternative to sliding window neural network (was: Object detect (or) image classification at specific locations in the frame)
There are many different problems in computer vision. Four of them are well described by the top image here:


Classification: Given an image, say what is on it (a single thing)
Classification+Localization: Given an image, say what is on it and draw an axis-aligned bounding box (AABB) around it
Object detection: Given an image, draw AABBs around every object and classify those objects
Semantic segmentation: See Survey of semantic segmentation
Instance segmentatation: Like semantic segmentation, but if there are multiple cats then they should be recognized as different objects.


Your question seems to be about object detection. The relevant papers here are:


SSD: Single Shot MultiBox Detector: Code
You Only Look Once: Unified, Real-Time Object Detection (YOLO): Website with video
YOLOv3


If you actually already have the regions, then you can simply perform classification on them. When you pad / scale / crop them, you can batch-predict them.